Gardner, Jacob R.

1. GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
   2018/09/28 by Jacob R. Gardner, Geoff Pleiss, Gardner, Jacob R. +7 · 91 citations
   Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Neural Networks and Applications
2. Simple Black-box Adversarial Attacks
   2019/05/17 by Guo, Chuan, Gardner, Jacob R., You, Yurong +2 · 13 citations
   #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Exact Gaussian Processes on a Million Data Points
   2019/03/19 by Ke Alexander Wang, Geoff Pleiss, Wang, Ke Alexander +9 · 5 citations
   Computer Science · Engineering · #Control Systems and Identification #Distributed #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Parallel #and Cluster Computing (cs.DC)
4. Preconditioning for Scalable Gaussian Process Hyperparameter Optimization
   2021/07/01 by Jonathan Wenger, Geoff Pleiss, Wenger, Jonathan +7 · 5 citations
   Computer Science · #Machine Learning and Data Classification #Advanced Neural Network Applications #Gaussian Processes and Bayesian Inference
5. Local Latent Space Bayesian Optimization over Structured Inputs
   2022/01/28 by Natalie Maus, Haydn T. Jones, Maus, Natalie +9 · 5 citations
   Computer Science · Materials Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Machine Learning in Materials Science
6. Product Kernel Interpolation for Scalable Gaussian Processes
   2018/02/24 by Gardner, Jacob R., Pleiss, Geoff, Wu, Ruihan +2 · 3 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Constant-Time Predictive Distributions for Gaussian Processes
   2018/03/16 by Pleiss, Geoff, Gardner, Jacob R., Weinberger, Kilian Q. +1 · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
8. Local Bayesian optimization via maximizing probability of descent
   2022/10/21 by Nguyen, Quan, Wu, Kaiwen, Gardner, Jacob R. +1 · 3 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
9. On the Convergence of Black-Box Variational Inference
   2023/05/24 by Kyurae Kim, Kim, Kyurae, Ji‐Su Oh +7 · 3 citations
   Computer Science · Mathematics · #Computation (stat.CO) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Signal Processing (eess.SP) #Statistical Methods and Inference #electronic engineering #information engineering
10. The Behavior and Convergence of Local Bayesian Optimization
    2023/05/24 by Kaiwen Wu, Kyurae Kim, Wu, Kaiwen +5 · 3 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
11. Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
    2020/06/29 by Shali Jiang, Jiang, Shali, Daniel Jiang +9 · 2 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Advanced Multi-Objective Optimization Algorithms #Gaussian Processes and Bayesian Inference
12. Understanding Stochastic Natural Gradient Variational Inference
    2024/06/04 by Kaiwen Wu, Jacob R. Gardner, Wu, Kaiwen +1 · 4 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
13. Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity
    2024/06/05 by Wentao Guo, Jikai Long, Guo, Wentao +21 · 3 citations
    Engineering · Mathematics · #Electromagnetic Simulation and Numerical Methods #Particle accelerators and beam dynamics #Numerical methods for differential equations
14. Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
    2023/07/27 by Kyurae Kim, Yi-An Ma, Kim, Kyurae +3 · 2 citations
    Business, Management and Accounting · Economics, Econometrics and Finance · #Computation (stat.CO) #Corporate Finance and Governance #Credit Risk and Financial Regulations #FOS: Computer and information sciences #Law, Economics, and Judicial Systems #Machine Learning (cs.LG) #Machine Learning (stat.ML)
15. Scaling Gaussian Processes with Derivative Information Using Variational Inference
    2021/07/08 by Misha Padidar, Padidar, Misha, Xinran Zhu +7 · 1 citation
    Computer Science · Engineering · #Advanced Multi-Objective Optimization Algorithms #Artificial Intelligence (cs.AI) #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
16. Parallel Support Vector Machines in Practice
    2014/04/03 by Stephen Tyree, Jacob R. Gardner, Tyree, Stephen +7 · 1 citation
    Computer Science · #Face and Expression Recognition #Anomaly Detection Techniques and Applications #Machine Learning and Algorithms
17. Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction
    2022/10/10 by Wang, Haoyu, Zhang, Hongming, Deng, Yuqian +3 · 1 citation
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
18. Large-Scale Gaussian Processes via Alternating Projection
    2023/10/26 by Kaiwen Wu, Jonathan Wenger, Wu, Kaiwen +7 · 1 citation
    Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and ELM #Machine Learning and Data Classification
19. Provably Scalable Black-Box Variational Inference with Structured Variational Families
    2024/01/19 by Ko, Joohwan, Kim, Kyurae, Kim, Woo Chang +1 · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
20. A Fast, Robust Elliptical Slice Sampling Implementation for Linearly Truncated Multivariate Normal Distributions
    2024/07/15 by Kaiwen Wu, Wu, Kaiwen, Jacob R. Gardner +1 · 1 citation
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
21. Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
    2024/11/01 by Jonathan Wenger, Kaiwen Wu, Wenger, Jonathan +9 · 1 citation
    Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Fault Detection and Control Systems #Target Tracking and Data Fusion in Sensor Networks
22. Learned Offline Query Planning via Bayesian Optimization
    2025/02/07 by Jeffrey Tao, Natalie Maus, Tao, Jeffrey +9 · 1 citation
    Computer Science · #Machine Learning and Algorithms #Advanced Database Systems and Queries #Data Management and Algorithms